AIMC Topic: Computer Security

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Ethical Challenges and Opportunities in Applying Artificial Intelligence to Cardiovascular Medicine.

The Canadian journal of cardiology
Much anticipation surrounds artificial intelligence's (AI) emergence as a promising tool in health care. It offers potential to revolutionise clinical practice through assistive and autonomous operation. The high prevalence of cardiac disease globall...

Optimized multi-head self-attention and gated-dilated convolutional neural network for quantum key distribution and error rate reduction.

Network (Bristol, England)
Quantum key distribution (QKD) is a secure communication method that enables two parties to securely exchange a secret key. The secure key rate is a crucial metric for assessing the efficiency and practical viability of a QKD system. There are severa...

Enhancement of cyber security in IoT based on ant colony optimized artificial neural adaptive Tensor flow.

Network (Bristol, England)
The Internet of Things (IoT) is a network that connects various hardware, software, data storage, and applications. These interconnected devices provide services to businesses and can potentially serve as entry points for cyber-attacks. The privacy o...

Computationally intelligent real-time security surveillance system in the education sector using deep learning.

PloS one
Real-time security surveillance and identity matching using face detection and recognition are central research areas within computer vision. The classical facial detection techniques include Haar-like, MTCNN, AdaBoost, and others. These techniques e...

Aligning the domains in cross domain model inversion attack.

Neural networks : the official journal of the International Neural Network Society
Model Inversion Attack reconstructs confidential training dataset from a target deep learning model. Most of the existing methods assume the adversary has an auxiliary dataset that has similar distribution with the private dataset. However, this assu...

A novel approach for APT attack detection based on feature intelligent extraction and representation learning.

PloS one
Advanced Persistent Threat (APT) attacks are causing a lot of damage to critical organizations and institutions. Therefore, early detection and warning of APT attack campaigns are very necessary today. In this paper, we propose a new approach for APT...

Advancements in intrusion detection: A lightweight hybrid RNN-RF model.

PloS one
Computer networks face vulnerability to numerous attacks, which pose significant threats to our data security and the freedom of communication. This paper introduces a novel intrusion detection technique that diverges from traditional methods by leve...

An optimized deep strategy for recognition and alleviation of DDoS attack in SD-IoT.

Network (Bristol, England)
The attacks like distributed denial-of-service (DDoS) are termed as severe defence issues in data centres, and are considered real network threat. These types of attacks can produce huge disturbances in information technologies. In addition, it is a ...

HyGloadAttack: Hard-label black-box textual adversarial attacks via hybrid optimization.

Neural networks : the official journal of the International Neural Network Society
Hard-label black-box textual adversarial attacks present a highly challenging task due to the discrete and non-differentiable nature of text data and the lack of direct access to the model's predictions. Research in this issue is still in its early s...

Adversarial Infrared Curves: An attack on infrared pedestrian detectors in the physical world.

Neural networks : the official journal of the International Neural Network Society
Deep neural network security is a persistent concern, with considerable research on visible light physical attacks but limited exploration in the infrared domain. Existing approaches, like white-box infrared attacks using bulb boards and QR suits, la...